spatstat (version 1.11-7)

spatstat: The Spatstat Package

Description

This is a summary of the features of spatstat, a package in R for the statistical analysis of spatial point patterns.

Getting Started

Type demo(spatstat) for an overall demonstration of the package.

For a readable introduction to spatstat, see the paper by Baddeley and Turner (2005a), available online.

Type demo(data) to see all the datasets available in the package.

FUNCTIONS AND DATASETS

Following is a summary of the main functions and datasets in the spatstat package. Alternatively an alphabetical list of all functions and datasets is available by typing library(help=spatstat).

For further information on any of these, type help(name) where name is the name of the function or dataset.

Type demo(data) to see all the datasets installed with the package.

CONTENTS:

ll{ I. Creating and manipulating data II. Exploratory Data Analysis III. Model fitting (cluster models) IV. Model fitting (Gibbs models) V. Tests and diagnostics VI. Documentation }

Details

spatstat is a package for the statistical analysis of spatial data. Currently, it deals mainly with the analysis of patterns of points in the plane. The points may carry `marks', and the spatial region in which the points were recorded may have arbitrary shape.

The package supports

• creation, manipulation and plotting of point patterns
• exploratory data analysis
• simulation of point process models
• parametric model-fitting
• hypothesis tests and diagnostics

The point process models to be fitted may be quite general Gibbs/Markov models; they may include spatial trend, dependence on covariates, and interpoint interactions of any order (i.e. not restricted to pairwise interactions). Models are specified by a formula in the R language, and are fitted using a single function ppm analogous to lm and glm. It is also possible to fit cluster process models by the method of minimum contrast.